A Comparative Study between Machine Learning and Deep Learning Algorithm for Network Intrusion Detection

Abstract

Network Intrusion Detection is a system that can monitor a network system to avoid malicious activities. One of the methods used for intrusion detection systems is using machine learning. Many pieces of research had proved that machine provides good detection in term of accuracy and performance. However, it can only be used with a smaller dataset other than the features can only be determined using human power. So, deep learning is applied to countermeasure the problem as it can form its own features without using human power other than can be tested with a larger dataset. This study aims to conduct a comparative study for network intrusion detection using machine learning and deep learning algorithm. The dataset that will be tested is CSE-CIC-IDS2018 using Support Vector Machine and Convolutional Neural Network.